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自动化诊断和评估高血压超声图像中心脏结构改变。

Automated Diagnosis and Assessment of Cardiac Structural Alteration in Hypertension Ultrasound Images.

机构信息

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.

Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore 599489, Singapore.

出版信息

Contrast Media Mol Imaging. 2022 May 29;2022:5616939. doi: 10.1155/2022/5616939. eCollection 2022.

DOI:10.1155/2022/5616939
PMID:35685669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9168207/
Abstract

Hypertension (HTN) is a major risk factor for cardiovascular diseases. At least 45% of deaths due to heart disease and 51% of deaths due to stroke are the result of hypertension. According to research on the prevalence and absolute burden of HTN in India, HTN positively correlated with age and was present in 20.6% of men and 20.9% of women. It was estimated that this trend will increase to 22.9% and 23.6% for men and women, respectively, by 2025. Controlling blood pressure is therefore important to lower both morbidity and mortality. Computer-aided diagnosis (CAD) is a noninvasive technique which can determine subtle myocardial structural changes at an early stage. In this work, we show how a multi-resolution analysis-based CAD system can be utilized for the detection of early HTN-induced left ventricular heart muscle changes with the help of ultrasound imaging. Firstly, features were extracted from the ultrasound imagery, and then the feature dimensions were reduced using a locality sensitive discriminant analysis (LSDA). The decision tree classifier with contourlet and shearlet transform features was later employed for improved performance and maximized accuracy using only two features. The developed model is applicable for the evaluation of cardiac structural alteration in HTN and can be used as a standalone tool in hospitals and polyclinics.

摘要

高血压(HTN)是心血管疾病的主要危险因素。至少 45%的心脏病死亡和 51%的中风死亡是由高血压引起的。根据印度高血压患病率和绝对负担的研究,高血压与年龄呈正相关,男性中有 20.6%,女性中有 20.9%患有高血压。据估计,到 2025 年,男性和女性的这一趋势将分别增加到 22.9%和 23.6%。因此,控制血压对于降低发病率和死亡率非常重要。计算机辅助诊断(CAD)是一种非侵入性技术,可以在早期确定微妙的心肌结构变化。在这项工作中,我们展示了如何利用基于多分辨率分析的 CAD 系统,借助超声成像检测早期高血压引起的左心室心肌变化。首先,从超声图像中提取特征,然后使用局部敏感判别分析(LSDA)减少特征维度。然后,使用决策树分类器结合轮廓和剪切波变换特征,以提高性能并仅使用两个特征实现最大准确性。开发的模型适用于评估高血压引起的心脏结构改变,可作为医院和诊所的独立工具使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/89cf6dfd23c3/CMMI2022-5616939.008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/d81f234f2012/CMMI2022-5616939.003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/371dab47a266/CMMI2022-5616939.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/fc8324fbe339/CMMI2022-5616939.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/a298d209b5e3/CMMI2022-5616939.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/89cf6dfd23c3/CMMI2022-5616939.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/dca8f26c8c12/CMMI2022-5616939.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/a22f9df9761f/CMMI2022-5616939.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/d81f234f2012/CMMI2022-5616939.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/0837d0fd74ab/CMMI2022-5616939.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/371dab47a266/CMMI2022-5616939.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/fc8324fbe339/CMMI2022-5616939.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/a298d209b5e3/CMMI2022-5616939.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a8/9168207/89cf6dfd23c3/CMMI2022-5616939.008.jpg

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